Molecular networks are the information processing devices of cells and organisms, transforming signals into[unreadable] coherent cellular responses. Networks are remarkably flexible and can re-configure in an adaptive response to[unreadable] perturbation. This ability is apparent at all levels - from fast epigenetic changes in response to environmental[unreadable] signals or developmental cues, to re-organization to accommodate pathological changes in cancer, to genetic[unreadable] changes underlying network evolution under selection. Reconfiguration is essential to networks' function as[unreadable] well as to their ability to evolve new functionality. We understand little, however, about how specific genetic[unreadable] and epigenetic changes allow novel functions to emerge in complex networks.[unreadable] Genomics has recently made it possible to collect massive datasets about temporally changing systems.[unreadable] Among molecular systems, regulatory networks controlling gene transcription are the most accessible for[unreadable] systems-scale analysis. The availability of scalable, cost-effective genomics approaches to systematically[unreadable] perturb and measure all levels of a transcriptional response along with sophisticated computational methods[unreadable] offer an extraordinary opportunity to study network function.[unreadable] We propose to develop a novel integrated experimental and computational framework to systematically[unreadable] decipher how regulatory networks assume novel adaptive functions through fast epigenetic changes or slow[unreadable] genetic changes. We will distinguish two types of temporal processes. For linear trajectories we will study[unreadable] epigenetic reconfiguration following a nutritional change, and genetic reconfiguration in yeast and cancer cells[unreadable] under selection. For lineages we will characterize the development of novel transcriptional states in the[unreadable] hematopoiesis ontogeny and the evolution of regulatory networks in the Ascomycota phylogeny. The work will[unreadable] unify disparate problems - including how cell adapts to changing growth conditions, how cancer develops, and[unreadable] how species evolve - under a single theoretical and methodological framework. It will help establish a new[unreadable] paradigm for genomics research by moving us from a static snapshot view to a fully dynamic perspective on[unreadable] molecular processes.